Scaling out is a common approach to dealing with big data in a distributed computing environment. Scaling out involves partitioning data across multiple database servers. With data partitioned, each database server can process its partition of data. In this way, the efficiencies of parallelism and load balance can be achieved through running multiple application service processes for a transaction over multiple database servers.
There is growing interest in putting traditional relational database systems and big data platforms together to provide customers a data center solution in a transparent and transactional way. The big data environment is a distributed system where there may be hundreds or thousands of data servers. Coordinating a large number of data servers with complex transactions and a mixed-workload environment is a challenge.